Comparison of COVID-19 Infection in Operating Room Staff During Two COVID-19 Waves Using Different Preventive Strategies in a Tertiary Care Hospital in Pakistan.

OBJECTIVE: To assess if limiting elective surgeries during specific pandemic phases significantly affected COVID-19 incidence among operating room (OR) staff. STUDY DESIGN: Retrospective cohort study. Place and Duration of the Study: Operation Theatre (OT), The Aga Khan University Hospital, Karachi, Pakistan, from May 2020 to 2021. METHODOLOGY: This retrospective study compared two pandemic waves: Wave 1, during which elective surgeries were restricted (REL), and Wave 2, during which elective surgeries were continued routinely (EL). Exposure levels were measured based on OR activity. Incidence rates were calculated per 100 OR staff, per 100 ORs, and per 100 surgeries for both Groups. RESULTS: No statistically significant difference emerged in COVID-19 incidence among OR staff between REL (13.8 per 100 staff) and EL (14.4 per 100 staff) Groups (p = 0.825). However, the EL Group exhibited a significantly lower incidence risk per running OR (5.6 per 100 ORs vs. REL's 12 per 100 ORs, p <0.001). Additionally, the EL Group showed a lower incidence per 100 surgeries (1.5 vs. REL's 2.9, p <0.002). CONCLUSION: Restricting elective surgeries during the early pandemic phase did not significantly reduce COVID-19 incidence among OR staff. Infections were primarily linked to interactions with colleagues and the community, emphasising the need for a balanced pandemic response considering patient care and the consequences of surgery restrictions. KEY WORDS: COVID-19 infection, Operating room staff, COVID-19 waves, COVID-19 transmission, Hospital epidemiology, Pandemic response.

International assessment results on non-NIOSH approved respirators by the national personal protective technology laboratory (NPPTL): a data note.

OBJECTIVES: Due to the COVID-19 pandemic and the shortage of the National Institute for Occupational Safety & Health (NIOSH)-approved N95 respirators, the Food and Drug Administration granted an Emergency Use Authorization to allow the use of non-NIOSH approved respirators provided that these respirators must undergo tests by a protocol of TEB-APR-STP-0059, similar methods of NIOSH standard testing procedure. This initiative safeguards the quality of respirators and the effectiveness of occupational protection. The dataset of all the testing results could benefit further analysis of COVID-19 infection rates in relation to different types of N95 respirators used and identify potential correlations of various test parameters in the testing system for validation. The analysis enhances understanding of the quality, effectiveness, and performance of N95 respirators in the prevention of respiratory infectious transmission and develops improved occupational safety measures. DATA DESCRIPTION: The dataset was transformed, transcribed, and compiled from the official testing data of non-NIOSH-approved N95 respirators reported in the NIOSH website under the Centers for the Disease Control and Prevention in the United States. The dataset included details of 7,413 testing results of N95 respirators (manufacturer, model, and maximum and minimum filtration efficiency) and test parameters (flow rate, initial filter resistance, and initial percent leakage). Supplementary items were added to increase the availability of data analysis and enhance the interpretability of the assessments of the quality of N95 respirators.

Prevalence, under-reporting, and epidemiological surveillance of COVID-19 in the Araguaína City of Brazil.

Asymptomatic and underreported individuals remain a source of coronafig disease 2019 (COVID-19) transmission to others. Data on the prevalence and epidemiological factors influencing transmission are fundamental for establishing control measures, especially in vulnerable regions such as the Amazon. This study aimed to determine the point prevalence and active infection of COVID-19 among the population in Araguaína, a Brazilian city located in the Amazon region, analyzed the socioeconomic and behavioral variables of a statistically representative sample of this population using an epidemiological survey, and identify the viral genomic diversity in the region. During the sixth epidemiological week of 2021 (February 8 to 12), samples of 497 inhabitants of the municipality asymptomatic for respiratory syndromes underwent reverse transcription-quantitative polymerase chain reaction and serological tests (immunoglobulin M and immunoglobulin G). A questionnaire collated data on socioeconomic factors, prevention measures, and health status history. The active infection rate was 6.2%, and the prevalence was 13.5% of the study population. Active infection cases were under-reported; each reported positive case represented 14-28 under-reported cases. Lineages P.2, P.1, and B.1.1 were detected. Working from home was a protective factor against the infection, and clinical signs of fever, dry cough, and loss of taste or smell were associated with testing positive (p <0.05). A descriptive analysis of the indicators revealed that the entire population was susceptible to the disease. Intensified vaccination strategies are required regardless of socioeconomic factors, health conditions, and preventive measures. Implementation of objective, comprehensive, and efficient management tools to minimize the spread of COVID-19 in this municipality can serve as a model for other regions of Brazil.

High SARS-CoV-2 Exposure in Rural Southern Mozambique After Four Waves of COVID-19: Community-Based Seroepidemiological Surveys.

BACKGROUND: Mozambique was one of many African countries with limited testing capacity for SARS-CoV-2. Serosurveys, an alternative to estimate the real exposure to understand the epidemiology and transmission dynamics, have been scarce in Mozambique. Herein, we aimed to estimate the age-specific seroprevalence of SARS-CoV-2 in the general population of the Manhiça District, at four time points, for evaluating dynamics of exposure and the impact of vaccination. METHODS: We conducted four community-based seroepidemiological surveys separated by 3 months between May 2021 and June 2022 to assess the prevalence of SARS-CoV-2 antibodies. An age-stratified (0-19, 20-39, 40-59, and ≥ 60 years) sample of 4810 individuals was randomly selected from demographic surveillance database, and their blood samples were analyzed using WANTAI SARS-CoV-2 IgG + IgM ELISA. Nasopharyngeal swabs from a subsample of 2209 participants were also assessed for active infection by RT-qPCR. RESULTS: SARS-CoV-2 seroprevalence increased from 27.6% in the first survey (May 2021) to 63.6%, 91.2%, and 91.1% in the second (October 2021), third (January 2022), and fourth (May 2022) surveys, respectively. Seroprevalence in individuals < 18 years, who were not eligible for vaccination, increased from 23.1% in the first survey to 87.1% in the fourth. The prevalence of active infection was below 10.1% in all surveys. CONCLUSIONS: A high seroprevalence to SARS-CoV-2 was observed in the study population, including individuals not eligible for vaccination at that time, particularly after circulation of the highly transmissible Delta variant. These data are important to inform decision making on the vaccination strategies in the context of pandemic slowdown in Mozambique.

How effective is the BNT162b2 mRNA vaccine against SARS-CoV-2 transmission and infection? A national programme analysis in Monaco, July 2021 to September 2022.

BACKGROUND: We quantified SARS-CoV-2 dynamics in different community settings and the direct and indirect effect of the BNT162b2 mRNA vaccine in Monaco for different variants of concern (VOC). METHODS: Between July 2021 and September 2022, we prospectively investigated 20,443 contacts from 6320 index cases using data from the Monaco COVID-19 Public Health Programme. We calculated secondary attack rates (SARs) in households (n = 13,877), schools (n = 2508) and occupational (n = 6499) settings. We used binomial regression with a complementary log-log link function to measure adjusted hazard ratios (aHR) and vaccine effectiveness (aVE) for index cases to infect contacts and contacts to be infected in households. RESULTS: In households, the SAR was 55% (95% CI 54-57) and 50% (48-51) among unvaccinated and vaccinated contacts, respectively. The SAR was 32% (28-36) and 12% (10-13) in workplaces, and 7% (6-9) and 6% (3-10) in schools, among unvaccinated and vaccinated contacts respectively. In household, the aHR was lower in contacts than in index cases (aHR 0.68 [0.55-0.83] and 0.93 [0.74-1.1] for delta; aHR 0.73 [0.66-0.81] and 0.89 [0.80-0.99] for omicron BA.1&2, respectively). Vaccination had no significant effect on either direct or indirect aVE for omicron BA.4&5. The direct aVE in contacts was 32% (17, 45) and 27% (19, 34), and for index cases the indirect aVE was 7% (- 17, 26) and 11% (1, 20) for delta and omicron BA.1&2, respectively. The greatest aVE was in contacts with a previous SARS-CoV-2 infection and a single vaccine dose during the omicron BA.1&2 period (45% [27, 59]), while the lowest were found in contacts with either three vaccine doses (aVE - 24% [- 63, 6]) or one single dose and a previous SARS-CoV-2 infection (aVE - 36% [- 198, 38]) during the omicron BA.4&5 period. CONCLUSIONS: Protection conferred by the BNT162b2 mRNA vaccine against transmission and infection was low for delta and omicron BA.1&2, regardless of the number of vaccine doses and previous SARS-CoV-2 infection. There was no significant vaccine effect for omicron BA.4&5. Health authorities carrying out vaccination campaigns should bear in mind that the current generation of COVID-19 vaccines may not represent an effective tool in protecting individuals from either transmitting or acquiring SARS-CoV-2 infection.

A behaviour and disease transmission model: incorporating the Health Belief Model for human behaviour into a simple transmission model.

The health and economic impacts of infectious diseases such as COVID-19 affect all levels of a community from the individual to the governing bodies. However, the spread of an infectious disease is intricately linked to the behaviour of the people within a community since crowd behaviour affects individual human behaviour, while human behaviour affects infection spread, and infection spread affects human behaviour. Capturing these feedback loops of behaviour and infection is a well-known challenge in infectious disease modelling. Here, we investigate the interface of behavioural science theory and infectious disease modelling to explore behaviour and disease (BaD) transmission models. Specifically, we incorporate a visible protective behaviour into the susceptible-infectious-recovered-susceptible (SIRS) transmission model using the socio-psychological Health Belief Model to motivate behavioural uptake and abandonment. We characterize the mathematical thresholds for BaD emergence in the BaD SIRS model and the feasible steady states. We also explore, under different infectious disease scenarios, the effects of a fully protective behaviour on long-term disease prevalence in a community, and describe how BaD modelling can investigate non-pharmaceutical interventions that target-specific components of the Health Belief Model. This transdisciplinary BaD modelling approach may reduce the health and economic impacts of future epidemics.

The COVID-19 pandemic "anthropause" decreased plastic ingestion in neotropic cormorants Nannopterum brasilianus in Lima, Peru.

Background: The anthropause during the recent COVID-19 pandemic provided a unique opportunity to examine the impact of human activity on seabirds. Lockdowns in Peru prevented people from visiting coastal areas, thereby reducing garbage disposal on beaches and the movement of microplastics into the ocean. This cessation of activities likely led to a temporary decrease in plastic pollution in coastal regions. We aimed to investigate this phenomenon in inshore-feeding neotropic cormorants (Nannopterum brasilianus) along the Circuito de Playas Costa Verde (CPCV), situated on the coastal strip of Lima, Peru (∼ 11 million people). Methods: We collected and analyzed fresh pellets along the CPCV before (over 11 months) and during the pandemic lockdowns (over 8 months). Results: Our findings revealed a significant reduction in the occurrence of plastic in pellets during the pandemic period (% Oc = 2.47, n = 647 pellets) compared to pre-pandemic conditions (% Oc = 7.13, n = 800 pellets). The most common plastic debris item found in the pellets was threadlike microplastic. Additionally, our study highlights the direct correlation between human presence on beaches and the quantity of microplastics (mainly threadlike) found in cormorant pellets. We suggest that the reintroduction of these materials into the sea, previously accumulated on the coast, is likely facilitated by the movement and activity of beachgoers toward the ocean.

Bayesian inference for the onset time and epidemiological characteristics of emerging infectious diseases.

Background: Emerging infectious diseases pose a significant threat to global public health. Timely detection and response are crucial in mitigating the spread of such epidemics. Inferring the onset time and epidemiological characteristics is vital for accelerating early interventions, but accurately predicting these parameters in the early stages remains challenging. Methods: We introduce a Bayesian inference method to fit epidemic models to time series data based on state-space modeling, employing a stochastic Susceptible-Exposed-Infectious-Removed (SEIR) model for transmission dynamics analysis. Our approach uses the particle Markov chain Monte Carlo (PMCMC) method to estimate key epidemiological parameters, including the onset time, the transmission rate, and the recovery rate. The PMCMC algorithm integrates the advantageous aspects of both MCMC and particle filtering methodologies to yield a computationally feasible and effective means of approximating the likelihood function, especially when it is computationally intractable. Results: To validate the proposed method, we conduct case studies on COVID-19 outbreaks in Wuhan, Shanghai and Nanjing, China, respectively. Using early-stage case reports, the PMCMC algorithm accurately predicted the onset time, key epidemiological parameters, and the basic reproduction number. These findings are consistent with empirical studies and the literature. Conclusion: This study presents a robust Bayesian inference method for the timely investigation of emerging infectious diseases. By accurately estimating the onset time and essential epidemiological parameters, our approach is versatile and efficient, extending its utility beyond COVID-19.

Public transit mobility as a leading indicator of COVID-19 transmission in 40 cities during the first wave of the pandemic.

Background: The rapid global emergence of the COVID-19 pandemic in early 2020 created urgent demand for leading indicators to track the spread of the virus and assess the consequences of public health measures designed to limit transmission. Public transit mobility, which has been shown to be responsive to previous societal disruptions such as disease outbreaks and terrorist attacks, emerged as an early candidate. Methods: We conducted a longitudinal ecological study of the association between public transit mobility reductions and COVID-19 transmission using publicly available data from a public transit app in 40 global cities from March 16 to April 12, 2020. Multilevel linear regression models were used to estimate the association between COVID-19 transmission and the value of the mobility index 2 weeks prior using two different outcome measures: weekly case ratio and effective reproduction number. Results: Over the course of March 2020, median public transit mobility, measured by the volume of trips planned in the app, dropped from 100% (first quartile (Q1)-third quartile (Q3) = 94-108%) of typical usage to 10% (Q1-Q3 = 6-15%). Mobility was strongly associated with COVID-19 transmission 2 weeks later: a 10% decline in mobility was associated with a 12.3% decrease in the weekly case ratio (exp(ß) = 0.877; 95% confidence interval (CI): [0.859-0.896]) and a decrease in the effective reproduction number (ß = -0.058; 95% CI: [-0.068 to -0.048]). The mobility-only models explained nearly 60% of variance in the data for both outcomes. The adjustment for epidemic timing attenuated the associations between mobility and subsequent COVID-19 transmission but only slightly increased the variance explained by the models. Discussion: Our analysis demonstrated the value of public transit mobility as a leading indicator of COVID-19 transmission during the first wave of the pandemic in 40 global cities, at a time when few such indicators were available. Factors such as persistently depressed demand for public transit since the onset of the pandemic limit the ongoing utility of a mobility index based on public transit usage. This study illustrates an innovative use of "big data" from industry to inform the response to a global pandemic, providing support for future collaborations aimed at important public health challenges.

Prevention of mother-to-child transmission of HIV service interruptions amid COVID-19 pandemic.

BACKGROUND:  The coronavirus disease 2019 (COVID-19) caused global disruptions in healthcare service delivery. The prevention of mother-to-child transmission (PMTCT) of human immunodeficiency viruses (HIV) services were also interrupted, threatening the attainment of Sustainable Development Goal 3. This article describes the PMTCT service interruptions experienced during the COVID-19 pandemic in Tshwane healthcare facilities. METHODS:  A descriptive phenomenological design was used to explore and describe the experiences of healthcare providers offering PMTCT services during COVID-19 in the Tshwane district, Gauteng province. Purposive sampling was used to recruit participants. Data were collected through in-depth interviews with 16 participants, and Colaizzi's data analysis steps were followed in analysing the findings. RESULTS:  Participants reported interruptions in PMTCT service delivery during the pandemic. Non-adherence to scheduled visits resulted in patients defaulting or not adhering to treatment regimens, high viral loads and mother-infant pairs' loss to follow-up. Other features of service disruption included late antenatal bookings, low client flow and delays in conducting deoxyribonucleic acid-polymerase chain reaction (DNA-PCR) testing in HIV-exposed babies. In addition, staff shortages occurred because of re-assignments to COVID-19-related activities. Study participants were psychologically affected by the fear of contracting COVID-19 and worked in a frustrating and stressful environment. CONCLUSION:  Improved community-based follow-up services are critical to enhance PMTCT service outcomes and prevent infant HIV infections.Contribution: The findings may influence policymakers in developing strategies to curb HIV infections among mothers and children during pandemics.

Temporal shifts in 24 notifiable infectious diseases in China before and during the COVID-19 pandemic.

The coronavirus disease 2019 (COVID-19) pandemic, along with the implementation of public health and social measures (PHSMs), have markedly reshaped infectious disease transmission dynamics. We analysed the impact of PHSMs on 24 notifiable infectious diseases (NIDs) in the Chinese mainland, using time series models to forecast transmission trends without PHSMs or pandemic. Our findings revealed distinct seasonal patterns in NID incidence, with respiratory diseases showing the greatest response to PHSMs, while bloodborne and sexually transmitted diseases responded more moderately. 8 NIDs were identified as susceptible to PHSMs, including hand, foot, and mouth disease, dengue fever, rubella, scarlet fever, pertussis, mumps, malaria, and Japanese encephalitis. The termination of PHSMs did not cause NIDs resurgence immediately, except for pertussis, which experienced its highest peak in December 2023 since January 2008. Our findings highlight the varied impact of PHSMs on different NIDs and the importance of sustainable, long-term strategies, like vaccine development.

Social contacts patterns relevant to the transmission of infectious diseases in Suzhou, China following the COVID-19 epidemic.

BACKGROUND: The COVID-19 pandemic has profoundly affected human social contact patterns, but there is limited understanding regarding the post-pandemic social contact patterns. Our objective is to quantitatively assess social contact patterns in Suzhou post-COVID-19. METHODS: We employed a diary design and conducted social contact surveys from June to October 2023, utilizing paper questionnaires. A generalized linear model was utilized to analyze the relationship between individual contacts and covariates. We examined the proportions of contact type, location, duration, and frequency. Additionally, age-related mixed matrices were established. RESULTS: The participants reported an average of 11.51 (SD 5.96) contact numbers and a total of 19.78 (SD 20.94) contact numbers per day, respectively. The number of contacts was significantly associated with age, household size, and the type of week. Compared to the 0-9 age group, those in the 10-19 age group reported a higher number of contacts (IRR = 1.12, CI: 1.01-1.24), while participants aged 20 and older reported fewer (IRR range: 0.54-0.67). Larger households (5 or more) reported more contacts (IRR = 1.09, CI: 1.01-1.18) and fewer contacts were reported on weekends (IRR = 0.95, CI: 0.90-0.99). School had the highest proportion of contact durations exceeding 4 h (49.5%) and daily frequencies (90.4%), followed by home and workplace. The contact patterns exhibited clear age-assortative mixing, with Q indices of 0.27 and 0.28. CONCLUSIONS: We assessed the characteristics of social contact patterns in Suzhou, which are essential for parameterizing models of infectious disease transmission. The high frequency and intensity of contacts among school-aged children should be given special attention, making school intervention policies a crucial component in controlling infectious disease transmission.

Alert for pharynx-centered gastrointestinal and respiratory cross-infection and cryptic cross-transmission routes of 2019-nCoV.

We proposed that the pharynx, as a common organ of the respiratory and digestive tracts, may be a respiratory and digestive tract cross cryptic transmission pathway for 2019-nCoV infection from the nasal cavities to the pharynx and lung, then to nasal cavities by aerosol (respiratory route) to the pharynx and the gastrointestinal tract, then to the oral cavity by feces (fecal-oral route) and to pharynx, lungs, or gastrointestinal tract.

SARS-CoV-2 variant introduction following spring break travel and transmission mitigation strategies.

BACKGROUND: University spring break carries a two-pronged SARS-CoV-2 variant transmission risk. Circulating variants from universities can spread to spring break destinations, and variants from spring break destinations can spread to universities and surrounding communities. Therefore, it is critical to implement SARS-CoV-2 variant surveillance and testing strategies to limit community spread before and after spring break to mitigate virus transmission and facilitate universities safely returning to in-person teaching. METHODS: We examined the SARS-CoV-2 positivity rate and changes in variant lineages before and after the university spring break for two consecutive years. 155 samples were sequenced across four time periods: pre- and post-spring break 2021 and pre- and post-spring break 2022; following whole genome sequencing, samples were assigned clades. The clades were then paired with positivity and testing data from over 50,000 samples. RESULTS: In 2021, the number of variants in the observed population increased from four to nine over spring break, with variants of concern being responsible for most of the cases; Alpha percent composition increased from 22.2% to 56.4%. In 2022, the number of clades in the population increased only from two to three, all of which were Omicron or a sub-lineage of Omicron. However, phylogenetic analysis showed the emergence of distantly related sub-lineages. 2022 saw a greater increase in positivity than 2021, which coincided with a milder mitigation strategy. Analysis of social media data provided insight into student travel destinations and how those travel events may have impacted spread. CONCLUSIONS: We show the role that repetitive testing can play in transmission mitigation, reducing community spread, and maintaining in-person education. We identified that distantly related lineages were brought to the area after spring break travel regardless of the presence of a dominant variant of concern.

Reducing Transmission of Airborne Respiratory Pathogens: A New Beginning as the COVID-19 Emergency Ends.

BACKGROUND: In response to the COVID-19 pandemic, new evidence-based strategies have emerged for reducing transmission of respiratory infections through management of indoor air. OBJECTIVES: This paper reviews critical advances that could reduce the burden of disease from inhaled pathogens and describes challenges in their implementation. DISCUSSION: Proven strategies include assuring sufficient ventilation, air cleaning by filtration, and air disinfection by germicidal ultraviolet (UV) light. Layered intervention strategies are needed to maximize risk reduction. Case studies demonstrate how to implement these tools while also revealing barriers to implementation. Future needs include standards designed with infection resilience and equity in mind, buildings optimized for infection resilience among other drivers, new approaches and technologies to improve ventilation, scientific consensus on the amount of ventilation needed to achieve a desired level of risk, methods for evaluating new air-cleaning technologies, studies of their long-term health effects, workforce training on ventilation systems, easier access to federal funds, demonstration projects in schools, and communication with the public about the importance of indoor air quality and actions people can take to improve it. https://doi.org/10.1289/EHP13878.

Applications of Quantitative Microbial Risk Assessment to Respiratory Pathogens and Implications for Uptake in Policy: A State-of-the-Science Review.

BACKGROUND: Respiratory tract infections are major contributors to the global disease burden. Quantitative microbial risk assessment (QMRA) holds potential as a rapidly deployable framework to understand respiratory pathogen transmission and inform policy on infection control. OBJECTIVES: The goal of this paper was to evaluate, motivate, and inform further development of the use of QMRA as a rapid tool to understand the transmission of respiratory pathogens and improve the evidence base for infection control policies. METHODS: We conducted a literature review to identify peer-reviewed studies of complete QMRA frameworks on aerosol inhalation or contact transmission of respiratory pathogens. From each of the identified studies, we extracted and summarized information on the applied exposure model approaches, dose-response models, and parameter values, including risk characterization. Finally, we reviewed linkages between model outcomes and policy. RESULTS: We identified 93 studies conducted in 16 different countries with complete QMRA frameworks for diverse respiratory pathogens, including SARS-CoV-2, Legionella spp., Staphylococcus aureus, influenza, and Bacillus anthracis. Six distinct exposure models were identified across diverse and complex transmission pathways. In 57 studies, exposure model frameworks were informed by their ability to model the efficacy of potential interventions. Among interventions, masking, ventilation, social distancing, and other environmental source controls were commonly assessed. Pathogen concentration, aerosol concentration, and partitioning coefficient were influential exposure parameters as identified by sensitivity analysis. Most (84%, n=78) studies presented policy-relevant content including a) determining disease burden to call for policy intervention, b) determining risk-based threshold values for regulations, c) informing intervention and control strategies, and d) making recommendations and suggestions for QMRA application in policy. CONCLUSIONS: We identified needs to further the development of QMRA frameworks for respiratory pathogens that prioritize appropriate aerosol exposure modeling approaches, consider trade-offs between model validity and complexity, and incorporate research that strengthens confidence in QMRA results. https://doi.org/10.1289/EHP12695.

Common cold viruses circulating in children threaten wild chimpanzees through asymptomatic adult carriers.

Reverse zoonotic respiratory diseases threaten great apes across Sub-Saharan Africa. Studies of wild chimpanzees have identified the causative agents of most respiratory disease outbreaks as "common cold" paediatric human pathogens, but reverse zoonotic transmission pathways have remained unclear. Between May 2019 and August 2021, we conducted a prospective cohort study of 234 children aged 3-11 years in communities bordering Kibale National Park, Uganda, and 30 adults who were forest workers and regularly entered the park. We collected 2047 respiratory symptoms surveys to quantify clinical severity and simultaneously collected 1989 nasopharyngeal swabs approximately monthly for multiplex viral diagnostics. Throughout the course of the study, we also collected 445 faecal samples from 55 wild chimpanzees living nearby in Kibale in social groups that have experienced repeated, and sometimes lethal, epidemics of human-origin respiratory viral disease. We characterized respiratory pathogens in each cohort and examined statistical associations between PCR positivity for detected pathogens and potential risk factors. Children exhibited high incidence rates of respiratory infections, whereas incidence rates in adults were far lower. COVID-19 lockdown in 2020-2021 significantly decreased respiratory disease incidence in both people and chimpanzees. Human respiratory infections peaked in June and September, corresponding to when children returned to school. Rhinovirus, which caused a 2013 outbreak that killed 10% of chimpanzees in a Kibale community, was the most prevalent human pathogen throughout the study and the only pathogen present at each monthly sampling, even during COVID-19 lockdown. Rhinovirus was also most likely to be carried asymptomatically by adults. Although we did not detect human respiratory pathogens in the chimpanzees during the cohort study, we detected human metapneumovirus in two chimpanzees from a February 2023 outbreak that were genetically similar to viruses detected in study participants in 2019. Our data suggest that respiratory pathogens circulate in children and that adults become asymptomatically infected during high-transmission times of year. These asymptomatic adults may then unknowingly carry the pathogens into forest and infect chimpanzees. This conclusion, in turn, implies that intervention strategies based on respiratory symptoms in adults are unlikely to be effective for reducing reverse zoonotic transmission of respiratory viruses to chimpanzees.

Impact of interventions to reduce nosocomial transmission of SARS-CoV-2 in English NHS Trusts: a computational modelling study.

BACKGROUND: Prior to September 2021, 55,000-90,000 hospital inpatients in England were identified as having a potentially nosocomial SARS-CoV-2 infection. This includes cases that were likely missed due to pauci- or asymptomatic infection. Further, high numbers of healthcare workers (HCWs) are thought to have been infected, and there is evidence that some of these cases may also have been nosocomially linked, with both HCW to HCW and patient to HCW transmission being reported. From the start of the SARS-CoV-2 pandemic interventions in hospitals such as testing patients on admission and universal mask wearing were introduced to stop spread within and between patient and HCW populations, the effectiveness of which are largely unknown. MATERIALS/METHODS: Using an individual-based model of within-hospital transmission, we estimated the contribution of individual interventions (together and in combination) to the effectiveness of the overall package of interventions implemented in English hospitals during the COVID-19 pandemic. A panel of experts in infection prevention and control informed intervention choice and helped ensure the model reflected implementation in practice. Model parameters and associated uncertainty were derived using national and local data, literature review and formal elicitation of expert opinion. We simulated scenarios to explore how many nosocomial infections might have been seen in patients and HCWs if interventions had not been implemented. We simulated the time period from March-2020 to July-2022 encompassing different strains and multiple doses of vaccination. RESULTS: Modelling results suggest that in a scenario without inpatient testing, infection prevention and control measures, and reductions in occupancy and visitors, the number of patients developing a nosocomial SARS-CoV-2 infection could have been twice as high over the course of the pandemic, and over 600,000 HCWs could have been infected in the first wave alone. Isolation of symptomatic HCWs and universal masking by HCWs were the most effective interventions for preventing infections in both patient and HCW populations. Model findings suggest that collectively the interventions introduced over the SARS-CoV-2 pandemic in England averted 400,000 (240,000 - 500,000) infections in inpatients and 410,000 (370,000 - 450,000) HCW infections. CONCLUSIONS: Interventions to reduce the spread of nosocomial infections have varying impact, but the package of interventions implemented in England significantly reduced nosocomial transmission to both patients and HCWs over the SARS-CoV-2 pandemic.

The Role of Human Mobility Flow in the Region-to-Region Spread of Respiratory Syncytial Virus Infection among Infants: An Infographic Analysis.

The region-to-region spread of human infectious diseases is considered to be dependent on the human mobility flow (HMF). However, it has been hard to obtain the evidence for this. Since the onset of the coronavirus disease 2019 (COVID-19) pandemic in Japan 2020, the government has enforced countermeasures against COVID-19 nationwide, namely the restriction of personal travelling, universal masking, and hand hygiene. As a result, the spread of acute respiratory infections had been effectively controlled. However, COVID-19 as well as pediatric respiratory syncytial virus (RSV) infections were not well-controlled. The region-to-region spread of pediatric RSV infections in 2020-2021 was recognizable unlike those in 2018 and 2019. In this study, we investigated the correlation between the trend of regional reports of the pediatric RSV infections and the HMF based on cellular phone signal data. Upon closer examination of both epidemiological trend and HMF data, the spread of pediatric RSV infection from one region to another was logically explained by HMF, which would serve as the evidence of the dependence of regional transmission on HMF. This is the first solid evidence where this correlation has been clearly observed for the common respiratory infections. While social implementation of infection control measures has successfully suppressed the droplet-mediated respiratory infections, such as influenza, but not the airborne infections, it was suggested that the aerosol transmission and adult asymptomatic carrier were involved in the transmission of RSV akin to COVID-19.

New framework to assess tracing and testing based on South Korea's response to COVID-19.

South Korea's remarkable success in controlling the spread of COVID-19 during the pre-Omicron period was based on extensive contact tracing and large-scale testing. Here we suggest a general criterion for tracing and testing based on South Korea's experience, and propose a new framework to assess tracing and testing. We reviewed papers on South Korea's response to COVID-19 to capture its concept of tracing and testing. South Korea expanded its testing capabilities to enable group tracing combined with preemptive testing, and to conduct open testing. According to our proposed model, COVID-19 cases are classified into 4 types: confirmed in quarantine, source known, source unknown, and unidentified. The proportion of the first two case types among confirmed cases is defined as "traced proportion", and used as the indicator of tracing and testing effectiveness. In conclusion, South Korea successfully suppressed COVID-19 transmission by maintaining a high traced proportion (> 60%) using group tracing in conjunction with preemptive testing as a complementary strategy to traditional contact tracing.